Molecular Interaction Maps and Analysis of Bioregulatory

分子相互作用图谱和生物调节分析

• 批准号: 7291872
• 负责人: mirit aladjem
• 金额: --
• 依托单位: DIVISION OF BASIC SCIENCES - NCI
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/7291872
• 关键词: Molecular; Interaction; Maps; Analysis; Bioregulatory

Knowledge about molecules that regulate cell growth has increased exponentially in recent years, but our ability to make sense of this detailed information has not. Moreover, although chromatin is a major target for cell cycle signaling, very little is known about how cells respond to these signals at the chromatin level. Our studies probe into this missing link through the analysis of molecular factors that determine the site and the timing of DNA replication. More details about these studies are provided in the description of Project 1, DNA replication studies in mammalian cells. In parallel, we are engaged in a collaborative effort to depict cellular signaling networks that control the mammalian cell cycle. To learn more about how bio-regulatory network control the cell cycle in normal and cancer cells, we collaborate with a crossdisciplinary team to generate electronic molecular interaction maps, which show the behavior of cell cycle regulatory pathways during normal growth and under conditions that perturb the cell cycle. These efforts help develop bioinformatics tools that organize large collections of facts, including descriptions of networks of interacting regulatory molecules, multi-protein complexes, protein modifications (e.g. phosphorylations), etc.. One of the main stumbling blocks to organizing molecular knowledge is the lack of a common language that allows scientists to integrate data in a clear, standardized, and preferably computer-readable format. To that end, we implemented the Molecular Interaction Map (MIM) language, a diagrammatic annotation first proposed by Kurt Kohn, which encodes molecular information in the form of diagrams (molecular interaction maps or MIMs). These MIMs are used to represent and analyze molecular interactions in the same way as circuit diagrams are used to trouble-shoot electronic devices. Investigators usually describe biochemical pathways in cartoon-like diagrams, but these representations of molecular interactions are often incomplete and ambiguous. For example, an arrow between two components could signify an increase in quantity, an increase in activity, or a modification of one molecule by the other. In addition, enzymes in bioregulatory networks are often substrates of other enzymes, and molecules are often subject to modifications that change their binding or enzymatic capabilities. Moreover, regulatory proteins can form multi-molecular complexes, which have different activities, depending on their composition and modifications. Finally, each domain within regulatory molecules may have its own binding, modification, and/or enzymatic functions. Thus, a molecule's activity and interaction capabilities may depend on its modification state, and on the other molecules to which it may be bound. All of these interactions must be taken into account for a full understanding of the system. In the MIM language, we use a small number of defined unambiguous graphical symbols to portray each type of molecular interaction. Each molecule is represented in a single place in a diagram, and interactions between molecules are specified by arrows or bars at the end of connecting lines. Because modified molecules and multi-molecular complexes may have different properties than the original molecules, the outcome of each interaction (such as a phosphorylated molecule, or a multi-molecular complex) is depicted as a circle, or "node" on an interaction line. These nodes are treated in a way that allows them to form more interactions and extend the network. The symbols and conventions used in the language, as well as examples of MIMs, can be accessed at our website: http://discover.nci.nih.gov/mim and in an article describing the principles of the MIM language. The graphical MIM language allows a simultaneous view of many interactions involving any given molecule. It can portray competing interactions, which are common in bioregulatory networks.

近年来，关于调节细胞生长的分子的知识呈指数级增长，但我们理解这些详细信息的能力却没有增长。此外，尽管染色质是细胞周期信号传导的主要靶点，但我们对细胞如何在染色质水平上对这些信号作出反应知之甚少。我们的研究通过分析决定DNA复制位点和时间的分子因素来探索这一缺失的环节。关于这些研究的更多细节，请参见项目1，哺乳动物细胞DNA复制研究的描述。与此同时，我们正在合作研究控制哺乳动物细胞周期的细胞信号网络。